将Pandas DataFrame切片为新的DataFrame [英] Slicing a Pandas DataFrame into a new DataFrame

问题描述

我想用布尔索引对DataFrame进行切片以获取副本，然后独立于原始DataFrame在该副本上执行操作.

I would like to slice a DataFrame with a Boolean index obtaining a copy, and then do stuff on that copy independently of the original DataFrame.

从此答案来看，使用.loc使用布尔数组选择时，我会得到一个副本，但是，如果我尝试更改副本，则SettingWithCopyWarning会妨碍您.那么这将是正确的方法吗?

Judging from this answer, selecting with .loc using a Boolean array will hand me back a copy, but then, if I try to change the copy, SettingWithCopyWarning gets in the way. Would this then be the correct way:

import numpy as np
import pandas as pd
d1 = pd.DataFrame(np.random.randn(10, 5), columns=['a', 'b', 'c', 'd', 'e'])
# create a new dataframe from the sliced copy
d2 = pd.DataFrame(d1.loc[d1.a > 1, :])
# do stuff with d2, keep d1 unchanged

推荐答案

您需要 copy 和 boolean indexing ，不需要新的DataFrame构造函数:

d2 = d1[d1.a > 1].copy()

警告说明:

如果稍后在d2中修改值，您会发现修改不会传播回原始数据(d1)，并且Pandas会发出警告.

If you modify values in d2 later you will find that the modifications do not propagate back to the original data (d1), and that Pandas does warning.

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